This paper demonstrates the successful implementation of an artificial neural network to accurately predict the designated thermal radiation distance for jet fire, early pool fire, and late pool fire hazard consequence analysis. Specifically, integrated feedforward neural network models employing the backpropagation Levenberg–Marquardt algorithm were trained using data sets obtained through separate PHAST software simulations of 450 leak scenarios of 35 common flammable chemicals. For each fire model (jet, early, late pool), there are 11 input parameters spanning both chemical parameters and release conditions. Simulation data was randomly divided into 70% training, 15% validation, and 15% test sets to conduct cross-validation and provide an independent measure of predictive accuracy for the neural network models. Statistical values, namely, coefficient of determination (R 2) and mean-square error (MSE), are calculated to evaluate model regression performance. All three neural network predictive models achieved considerably accurate predictions of the logarithm format of the designated radiation effect distance. The models give an overall R 2 of 0.9930 and an MSE of 0.0022 for jet fire, an overall R 2 of 0.9909 and an MSE of 0.0016 for early pool fire, and an overall R 2 of 0.9899 and an MSE of 0.0015 for late pool fire.
The homogeneous phosphotungstic acid catalyzed N‐oxidation of alkylpyridines by hydrogen peroxide has important applications in pharmaceutical and fine chemical industries. Current industry practice is to employ a semibatch reactor with gradual dosing of hydrogen peroxide into an alkylpyridine/catalyst solution under isothermal conditions. However, due to lack of understanding of reaction mechanism and thermodynamic behavior, this system is subject to significant risk of flammability, fires and explosions due to hydrogen peroxide decomposition. In this study, we conducted semibatch N‐oxidation process in an isothermal reaction calorimeter (RC1) over a wide range of temperature, catalyst amount and oxidizer dosing rates. Reactor pressure, reaction heat generation rate and in situ FTIR spectra of liquid phase species were recorded in real‐time during experiments, and final product was quantified using HPLC and GC–MS analytical tools. We developed an integrated thermodynamic and kinetics model of homogeneous N‐oxidation reaction based on experimental results and past literature findings. More specifically, Wilson excess Gibbs model was employed to estimate activity coefficients of highly nonideal liquid mixture. We found ideal gas law was satisfactory in calculating incondensable oxygen pressure. First principle reaction mechanism and kinetics parameters of (a) catalytic N‐oxidation reaction; (b) catalytic hydrogen peroxide decomposition reaction; (c) noncatalytic N‐oxidation reaction; (d) noncatalytic hydrogen peroxide decomposition reaction was derived based on experimental findings of this study and past literature. The proposed integrated thermodynamic model and kinetics model successfully predicted highly nonlinear reactor pressure, species concentration and reaction enthalpy generation rate profile of homogenous catalytic N‐oxidation and H2O2 decomposition reaction. The optimal reactions conditions with maximum N‐oxide product yield and minimum reactor pressure and catalyst usage was theoretically identified and further verified by experiments. The obtained model can be used for inherently safer reactor design and applied to other homogeneous tungstic acid catalytic hydrogen peroxide oxidation processes.
Identification of inherently safer and intensified reaction conditions is a vital step for transformation of traditional batch/semibatch synthesis to continuous operation. Accelerating reactions is challenged by several safety and efficiency issues including thermal runaway risk, side reactions, final product degradation, and reactor overpressure. This work demonstrates the use of response surface methodology to identify inherently safer and more efficient intensified reaction conditions for 3-methylpyridine N-oxidation performed in a semibatch pressure-resistant isothermal calorimeter. The experimental conditions were selected to screen various operating-variable combinations using Box–Behnken design of experiments. Regression models were developed correlating the catalyst amount, oxidizer dosing-rate, and reaction temperature with reactor pressure and N-oxide yield; good agreement with experimental data obtained in the present study and from literature was achieved. Results indicate that, even when conducted in a semibatch mode, the reaction is inherently safer and more efficient under intensified conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.